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      <div class="title">prtClassCap/prtClassCap</div>
      <div class="helptext"><pre><!--helptext -->  <span class="helptopic">prtClassCap</span>  Central Axis projection classifier
 
     CLASSIFIER = <span class="helptopic">prtClassCap</span> returns a Cap classifier
 
     CLASSIFIER = <span class="helptopic">prtClassCap</span>(PROPERTY1, VALUE1, ...) constructs a
     <span class="helptopic">prtClassCap</span> object CLASSIFIER with properties as specified by
     PROPERTY/VALUE pairs.
 
     A <span class="helptopic">prtClassCap</span> object inherits all properties from the abstract class
     prtClass. In addition is has the following properties:
 
     w                 -  Central axis projection weights, set during
                          training
     threshold         -  Decision threshold, set during training
 
     Cap classifiers are a prototypical "weak" classification algorithm
     that find application in multiple meta-algorithms.  A good
     explanation of Cap classifiers can be found in:
 
     Breiman, Leo (2001). "Random Forests". Machine Learning 45 (1): 
     5&#x96;32.
 
     Note that the output of the run method of a <span class="helptopic">prtClassCap</span> classifier
     includes the process of applying the learned threshold to the
     linear projection, so the outputs are discrete valued.
 
     A <span class="helptopic">prtClassCap</span> object inherits the TRAIN, RUN, CROSSVALIDATE and 
     KFOLDS methods from prtAction. It also inherits the PLOT method 
     from prtClass.
 
     Example:
 
      TestDataSet = prtDataGenUniModal;       % Create some test and
      TrainingDataSet = prtDataGenUniModal;   % training data
      classifier = <span class="helptopic">prtClassCap</span>;              % Create a classifier
      classifier = classifier.train(TrainingDataSet);    % Train
      classified = run(classifier, TestDataSet);         % Test
      percentCorr = prtScorePercentCorrect(classified,TestDataSet);
      subplot(2,1,1);
      classifier.plot;
      subplot(2,1,2);
      [pf,pd] = prtScoreRoc(classified,TestDataSet);
      h = plot(pf,pd,'linewidth',3);
      title('ROC'); xlabel('Pf'); ylabel('Pd');</pre></div><!--after help -->
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